As the popularity of online video increases, so do the number of videos hosted on video streaming sites such as, for example, YouTube® and Netflix® to name a few. It is estimated that, on YouTube alone, over 4 billion videos are viewed each day, and that 300 hours of new video are uploaded to YouTube every minute. For users seeking to find specific content in a part of a video, largely gone are the days of simply rewinding and fast forwarding through it. A user seeking to review content in an online video presently has a number of search and scrubbing solutions. Certain video player software allows users to “scrub” through a video (i.e., move through the video timeline typically by dragging a pointer on a slider from left to right) whereby thumbnails of key frames of the video are shown. This enables a user to quickly scan the content of a video to see what is coming up or has gone before. FIG. 1 illustrates, in simplified form, a simplified example of a conventional, prior art video player 100, having a user interface 102, that is running on a processor-containing computer 104 (which could be a smart television, a desktop computer, a laptop computer, a tablet computer, a smart phone, a smart watch, or other computing device capable of playing video for a user in a video player). As is conventional, the computer will contain one or more processors, as well as RAM, ROM, some form of I/O, and non-volatile storage.
As shown in FIG. 1, and as is well known, the user interface 102 of the video player 100 includes interface controls such as a conventional Play/Pause button 106, a fast forward button 108, a rewind button 110, a stop button 112 and one or more auxiliary buttons, for example, a volume control button 114. The user interface 102 also includes a slider 116 via which the user can scrub through a video loaded into, or streaming to, the video player 100.
As shown in FIG. 1, the current video is paused at a point partially through the video, as indicated by a pointer 118 of the slider 116. The current frame of the paused video is displayed within the screen 120 of the video player 100 and shows a human figure 122 in the center, a series of buildings 124a, 124b, 124c, and a balloon 126 floating between the location of the figure 122 and one of the buildings 124a. In addition, the screen 120 contains a timeline 128 of the currently loaded video that includes a series of key frames 130a, 130b, 130c, 130d, 130e, 130f, 130g, 130h, 130i that correspond to some number of frames 130a, 130b, 130c, 130d of the video before the currently-displayed frame 130e and some number of frames 130f, 130g, 130h, 130i of the video after the currently-displayed frame 130e. In addition, with this particular user interface 102, the currently-displayed frame 130e is shown enlarged on the timeline. As can be seen in the subset of key frames 130a, 130b, 130c, 130d, 130e, 130f, 130g, 130h, 130i, the balloon 126 is traversing from the left side of the frame, behind the figure 122 and in front of the buildings 124a, 124b, 124c. If the user wanted to locate where in the video, for example, the balloon is above the second building 124b, they would move the pointer 118 of the slider 116 (in this case simply advance it to the right) until the specific frame 130h was located. Of course, if that frame 130h was not within the displayed portion of the timeline and its specific location was unknown, the user might have to move the pointer 118 back and forth along the slider 116 until the particular frame of interest was located.
While the display of key frames 130a-130i can assist a user in finding a desired part of a video, this type of searching can be time consuming and tedious and presents a problem because this approach is prone to having the user overshoot, or entirely miss, key frames of interest.
The above problem is compounded if the searching is to be done repeatedly for multiple videos. For example, it is presently not uncommon for old films to be digitized so that they can be made more broadly available for various purposes, including scholarly research. In doing so, when digitized, the videos may have some associated information logged for future reference relating to its content, but that information typically only reflects the major focus of the film and may not include minor details that are not noteworthy at the time, or of no interest per se. As a result, it is likewise not uncommon for a later researcher viewing a digitized video to notice someone, or something, previously unnoticed that is later recognized to be of significance, for example, the presence of a person long before they were famous or a detail that may aid in unraveling some long unsolved mystery. Such research efforts can require, a researcher to view countless hours of videos of potentially no relevance at all with the hope that they may possibly contain a few seconds of the desired person(s) or thing(s).
Thus, there is an ongoing and increasing problem involving the ability to more quickly and efficiently perform video searching.